CCAAK無料認定試験材料はこちらの56問題 [Q22-Q47]

CCAAK無料認定試験材料はこちらの56問題

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質問 # 22
Which statements are correct about partitions? (Choose two.)

A. A partition size is determined after the largest segment on a disk.
B. A partition in Kafka will be represented by a single segment on a disk.
C. A partition is comprised of one or more segments on a disk.
D. All partition segments reside in a single directory on a broker disk.

正解：C、D

質問 # 23
Which connector type takes data from a topic and sends it to an external data system?

A. Source Connector
B. Sink Connector
C. Streams Connector
D. SvsIog Connector

正解：B

解説：
A Sink Connector reads data from a Kafka topic and writes it to an external data system, such as a database, file system, or cloud service.

質問 # 24
You are managing a Kafka cluster with five brokers (broker id '0', '1','2','3','4') and three ZooKeepers. There are 100 topics, five partitions for each topic, and replication factor three on the cluster. Broker id '0' is currently the Controller, and this broker suddenly fails.
Which statements are correct? (Choose three.)

A. The number of Controllers should always be equal to the number of brokers alive in the cluster.
B. The Controller uses the epoch number to prevent a split brain scenario.
C. The Controller is responsible for reassigning partitions to the consumers in a Consumer Group.
D. Kafka uses ZooKeeper's ephemeral node feature to elect a controller.
E. The broker id is used as the epoch number to prevent a split brain scenario.
F. The Controller is responsible for electing Leaders among the partitions and replicas.

正解：B、D、F

解説：
Kafka relies on ZooKeeper's ephemeral nodes to detect if a broker (controller) goes down and to elect a new controller.
The controller manages partition leadership assignments and handles leader election when a broker fails.
The epoch number ensures coordination and avoids outdated controllers acting on stale data.

質問 # 25
Which secure communication is supported between the REST proxy and REST clients?

A. Kerberos
B. SCRAM
C. MD5
D. TLS (HTTPS)

正解：D

質問 # 26
What is the atomic unit of data in Kafka?

A. Offset
B. Topic
C. Message
D. Partition

正解：C

解説：
The message (also called a record) is the atomic unit of data in Kafka. It consists of a key, value, and optional headers and metadata. Messages are written to partitions and read by consumers.

質問 # 27
A company has an existing Kafka cluster running without SSL/TLS enabled. The customer wants to enable SSL on brokers to secure data in transit, but they would like to give applications connecting to this cluster some time to migrate to using SSL connection instead of putting a hard stop.
Which solution will meet the customer's requirements?

A. Enable SSL on the current listener, and do not implement SSL on application side.
B. Modify the advertised listeners setting on brokers to use SSL.
C. Enable SSL on the current Listener, and do not enable mTLS.
D. Create a new listener with SSL enabled.

正解：D

解説：
Kafka supports multiple listeners, allowing you to run PLAINTEXT and SSL simultaneously. By creating a new SSL-enabled listener (e.g., on a different port), existing applications can continue using PLAINTEXT while gradually migrating to the SSL listener. This approach avoids downtime and gives clients time to adapt without enforcing a hard cutover.

質問 # 28
Which option is a valid Kafka Topic cleanup policy? (Choose two.)

A. compact
B. default
C. delete
D. cleanup

正解：A、C

解説：
The delete policy deletes old log segments when they exceed the retention period or size.
The compact policy retains only the latest record for each key, enabling efficient key-based storage.

質問 # 29
You want to increase Producer throughput for the messages it sends to your Kafka cluster by tuning the batch size ('batch size') and the time the Producer waits before sending a batch ('linger.ms').
According to best practices, what should you do?

A. Increase 'batch.size' and increase 'linger.ms'
B. Decrease 'batch.size' and decrease 'linger.ms'
C. Increase 'batch.size' and decrease 'linger.ms'
D. Decrease 'batch.size' and increase 'linger.ms'

正解：A

解説：
Increasing batch.size allows the producer to accumulate more messages into a single batch, improving compression and reducing the number of requests sent to the broker.
Increasing linger.ms gives the producer more time to fill up batches before sending them, which improves batching efficiency and throughput.
This combination is a best practice for maximizing throughput, especially when message volume is high or consistent latency is not a strict requirement.

質問 # 30
An employee in the reporting department needs assistance because their data feed is slowing down. You start by quickly checking the consumer lag for the clients on the data stream.
Which command will allow you to quickly check for lag on the consumers?

A. bin/kafka-reassign-partitions.sh
B. bin/kafka-consumer-groups.sh
C. bin/kafka-consumer-lag.sh
D. bin/kafka-consumer-group-throughput.sh

正解：B

解説：
The kafka-consumer-groups.sh script is used to inspect consumer group details, including consumer lag, which indicates how far behind a consumer is from the latest data in the partition.
The typical usage is bin/kafka-consumer-groups.sh --bootstrap-server <broker> --describe --group <group_id>

質問 # 31
A broker in the Kafka cluster is currently acting as the Controller.
Which statement is correct?

A. It can have topic partitions.
B. All consumers are allowed to fetch messages only from this server.
C. It is given precedence for replication to and from replica followers.
D. It is responsible for sending leader information to all producers.

正解：A

解説：
The Controller broker is a regular broker that also takes on additional responsibilities for managing cluster metadata, such as leader elections and partition assignments. It still hosts topic partitions and participates in replication like any other broker.

質問 # 32
Kafka Connect is running on a two node cluster in distributed mode. The connector is a source connector that pulls data from Postgres tables (users/payment/orders), writes to topics with two partitions, and with replication factor two. The development team notices that the data is lagging behind.
What should be done to reduce the data lag*?
The Connector definition is listed below:
{
"name": "confluent-postgresql-source",
"connector class": "PostgresSource",
"topic.prefix": "postgresql_",
& nbsp;& nbsp;& nbsp;...
"db.name": "postgres",
"table.whitelist": "users.payment.orders",
"timestamp.column.name": "created_at",
"output.data format": "JSON",
"db.timezone": "UTC",
"tasks.max": "1"
}

A. Increase the number of Connect Nodes.
B. Increase the number of partitions.
C. Increase the replication factor and increase the number of Connect Tasks.
D. Increase the number of Connect Tasks (tasks max value).

正解：D

解説：
The connector is currently configured with "tasks.max": "1", which means only one task is handling all tables (users, payment, orders). This can create a bottleneck and lead to lag. Increasing tasks.max allows Kafka Connect to parallelize work across multiple tasks, which can pull data from different tables concurrently and reduce lag.

質問 # 33
How can load balancing of Kafka clients across multiple brokers be accomplished?

A. Replicas
B. Offsets
C. Connectors
D. Partitions

正解：D

解説：
Partitions are the primary mechanism for achieving load balancing in Kafka. When a topic has multiple partitions, Kafka clients (producers and consumers) can distribute the load across brokers hosting these partitions.

質問 # 34
An employee in the reporting department needs assistance because their data feed is slowing down. You start by quickly checking the consumer lag for the clients on the data stream.
Which command will allow you to quickly check for lag on the consumers?

A. bin/kafka-reassign-partitions.sh
B. bin/kafka-consumer-groups.sh
C. bin/kafka-consumer-lag.sh
D. bin/kafka-consumer-group-throughput.sh

正解：B

質問 # 35
You have a Kafka cluster with topics t1 and t2. In the output below, topic t2 shows Partition 1 with a leader "-1".
What is the most likely reason for this?
...
$ kafka-topics --zookeeper localhost:2181 --describe --topic t1
Topic:t1 PartitionCount 1 ReplicationFactor 1 Configs:
Topic: t1 Partition: 0 Leader: 0 Replicas: 0 Isr: 0
$ kafka-topics --zookeeper localhost:2181 --describe --topic t2
Topic:t2 PartitionCount 2 ReplicationFactor 1 Configs:
Topic: t2 Partition: 0 Leader: 0 Replicas: 0 Isr: 0
Topic: t2 Partition: 1 Leader: -1 Replicas: 1 Isr:

A. Leader shows "-1" while the log cleaner thread runs on Broker 1.
B. Broker 1 failed.
C. Compression has been enabled on Broker 1.
D. Broker 1 has another partition clashing with the same name.

正解：B

解説：
A Leader of -1 indicates that no broker is currently the leader for that partition. This usually happens when the only replica for that partition is unavailable, often due to the associated broker (in this case, Broker 1) failing or being offline. Kafka cannot elect a leader if no replica is in the in-sync replica (ISR) list, which leads to leader = -1.

質問 # 36
Per customer business requirements, a system's high availability is more important than message reliability.
Which of the following should be set?

A. The linger.ms should be set to '0'.
B. Message retention.ms should be set to -1.
C. The number of brokers in the cluster should be always odd (3, 5. 7 and so on).
D. Unclean leader election should be enabled.

正解：D

解説：
Enabling unclean leader election allows Kafka to elect a non-in-sync replica as leader if all in-sync replicas are unavailable. This sacrifices message reliability (possible data loss) in favor of high availability, aligning with the requirement.

質問 # 37
By default, what do Kafka broker network connections have?

A. No encryption, no authorization, but have authentication
B. Encryption and authentication, but no authorization
C. No encryption, no authentication and no authorization
D. Encryption, but no authentication or authorization

正解：C

解説：
By default, Kafka brokers use the PLAINTEXT protocol for network communication. This means:
* No encryption - data is sent in plain text.
* No authentication - any client can connect without verifying identity.
* No authorization - there are no access control checks by default.
Security features like TLS, SASL, and ACLs must be explicitly configured.

質問 # 38
A customer has a use case for a ksqlDB persistent query. You need to make sure that duplicate messages are not processed and messages are not skipped.
Which property should you use?

A. ksql.streams auto offset.reset=earliest
B. ksql.fail.on.production.error=false
C. processing.guarantee=exactly_once
D. ksql.streams auto.offset.reset=latest

正解：C

解説：
processing.guarantee=exactly_once ensures that messages are processed exactly once by ksqlDB, preventing both duplicates and message loss.

質問 # 39
What is the relationship between topics and partitions? (Choose two.)

A. Atopic always has one partition.
B. Atopic may have more than one partition.
C. A partition is always linked to a single topic.
D. There is no relationship between topics and partitions.
E. A partition may have more than one topic.

正解：B、C

解説：
Kafka topics are split into one or more partitions to enable parallelism and scalability.
Each partition belongs to exactly one topic; it cannot span multiple topics.

質問 # 40
Your Kafka cluster has four brokers. The topic t1 on the cluster has two partitions, and it has a replication factor of three. You create a Consumer Group with four consumers, which subscribes to t1.
In the scenario above, how many Controllers are in the Kafka cluster?

A. One
B. two
C. Four
D. three

正解：A

解説：
In a Kafka cluster, only one broker acts as the Controller at any given time. The Controller is responsible for managing cluster metadata, such as partition leadership and broker status. Even if the cluster has multiple brokers (in this case, four), only one is elected as the Controller, and others serve as regular brokers. If the current Controller fails, another broker is automatically elected to take its place.

質問 # 41
How does Kafka guarantee message integrity after a message is written on a disk?

A. A message can be edited by the producer, producing to the message offset.
B. A message cannot be altered once it has been written.
C A message can be grouped with message sharing the same key to improve read performance
C. Only message metadata can be altered using command line (CLI) tools.

正解：B

解説：
Kafka ensures message immutability for data integrity. Once a message is written to a Kafka topic and persisted to disk, it cannot be modified. This immutability guarantees that consumers always receive the original message content, which is critical for auditability, fault tolerance, and data reliability.

質問 # 42
The Consumer property 'auto offset reset' determines what to do if there is no valid offset for a Consumer Group.
Which scenario is an example of a valid offset and therefore the 'auto.offset.reset' does NOT apply?

A. The Consumer offset is less than the smallest offset in the partition (log start offset).
B. The Consumer offset is greater than the last offset in the partition (log end offset).
C. When an offset points to a message that has been removed by compaction but is still within the current partition.offset range.
D. The Consumer Group started for the first time.

正解：C

解説：
In this scenario, the offset itself is still valid, even though the record at that offset was compacted away. The consumer can continue consuming from the next available record. Therefore, auto.offset.reset does NOT apply, because there is a valid offset present.

質問 # 43
A topic 'recurring payments' is created on a Kafka cluster with three brokers (broker id '0', '1', '2') and nine partitions. The 'min.insync replicas' is set to three, and producer is set with 'acks' as 'all'. Kafka Broker with id '0' is down.
Which statement is correct?

A. Producers and consumers will have no impact on six of the nine partitions.
B. Consumers can read committed messages from partitions on broker id T, "2\
C. Producers will only be able to write messages to the topic where the Leader for the partition is on Broker id T.
D. Producers can write messages to all the partitions, because new leaders for the partitions will be elected.

正解：A

解説：
With 9 partitions spread across 3 brokers, each broker typically hosts 3 leaders (assuming even distribution). When Broker 0 fails, the partitions for which it was leader will elect new leaders on brokers 1 or 2 if enough in-sync replicas (ISRs) remain. But since min.insync.replicas=3 and only 2 brokers are up, no partition can meet the minimum in-sync replica requirement, so producers with acks=all will fail to write. However, for partitions where Broker 0 is not the leader, consumers can still read committed messages. Given that only 3 partitions likely had Broker 0 as leader, six partitions remain accessible for reads, but not writes.

質問 # 44
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